So here I am in the Amazon Kinesis service.
And I wanna show you just the options
for Kinesis data analytics.
So here it is.
So we have two different kinds of things.
You can either create a streaming application
or go into the studio.
The streaming application is actually just
all leveraging app Apache Flink.
This is the case analytics for Apache Flink.
You choose a runtime version
for Apache Flink that's supported
and then you can have the application name.
And then, at some point,
you need to enter your production information.
And this would create a streaming application
that you can use on AWS.
And so you would need to actually upload then
your application here.
As we see when we get there
and we don't have any Apache Flink application available
to us, because this is quite complex, right?
Then you can run and you can even monitor it
using the Apache Flink dashboard.
So this service is to create Apache Flink applications.
And actually, if you wanted to just do one of analysis
you can open a studio notebook
and this will just quickly create a notebook
where you can start running your streaming applications
again, leveraging Apache Flink.
Okay. So this I will not do.
And then where is the Apache,
where is the Amazon Kinesis data analytics
for SQL applications?
Well, it's on the left hand side
and this is where it would be.
So you would find it under the SQL applications legacy
and now they recommend that you use all the time
Kinesis data analytics studio and Apache Flink?
But if you wanted to, for example, read from
Kinesis Data Firehose, you would create a SQL applications
in the legacy form and you would enter actually
the application name and it did create one.
And then once you've define your application name,
you can actually go to realtime analytics
and write the kind of SQL you want to do
for this application, okay?
So it's just an overview.
You don't need to know anything
about Kinesis data analytics for this exam
but I wanna show you the options,
give you a quick introduction.
And so you could visualize it as well on the console.
So that's it for this lecture.
I hope you liked it.
And I will see you in the next lecture.